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Grid Search for Lowest Root Mean Squared Error in Predicting Optimal Sensor Location in Protected Cultivation Systems [PDF]
Frontiers in Plant Science, 2022 Irregular changes in the internal climates of protected cultivation systems can prevent attainment of optimal yield when the environmental conditions are not adequately monitored and controlled.
Daniel Dooyum Uyeh +12 more
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Correcting the Bias of the Root Mean Squared Error of Approximation Under Missing Data [PDF]
Methodology, 2021 Missing data are ubiquitous in psychological research. They may come about as an unwanted result of coding or computer error, participants' non-response or absence, or missing values may be intentional, as in planned missing designs.
Cailey E. Fitzgerald +4 more
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Interpolatory model reduction of dynamical systems with root mean squared error
IFAC-PapersOnLineThe root mean squared error is an important measure used in a variety of applications such as structural dynamics and acoustics to model averaged deviations from standard behavior. For large-scale systems, simulations of this quantity quickly become computationally prohibitive.
Steffen W R Werner
exaly +3 more sources
Agriculture, 2022 To ensure continued food security and economic development in Africa, it is very important to address and adapt to climate change. Excessive dependence on rainfed agricultural production makes Africa more vulnerable to climate change effects.
Chimango Nyasulu +4 more
doaj +1 more source
Root mean square error (RMSE) or mean absolute error (MAE)? [PDF]
Geoscientific Model Development, 2014 Abstract. Both the root mean square error (RMSE) and the mean absolute error (MAE) are regularly employed in model evaluation studies. Willmott and Matsuura (2005) have suggested that the RMSE is not a good indicator of average model performance and might be a misleading indicator of average error and thus the MAE would be a better metric for that ...
T. Chai, R. R. Draxler
openaire +4 more sources
Genomes to Fields 2022 Maize genotype by Environment Prediction Competition
BMC Research Notes, 2023 Objectives The Genomes to Fields (G2F) 2022 Maize Genotype by Environment (GxE) Prediction Competition aimed to develop models for predicting grain yield for the 2022 Maize GxE project field trials, leveraging the datasets previously generated by this ...
Dayane Cristina Lima +33 more
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Implementation of the Fuzzy Tsukamoto Method for Office Stationery Estimation Stock System
Jurnal Riset Informatika, 2022 Information technology supports the company's operational activities in recording incoming goods, outgoing goods, and existing inventory. PT. Mitraniaga Distribusindo is a company engaged in food distribution, which includes supporting aspects for smooth
Tedy Rukmana +2 more
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Modeling nanofluid viscosity: comparing models and optimizing feature selection—a novel approach
Bulletin of the National Research Centre, 2023 Background The accurate prediction of viscosity in nanofluids is essential for comprehending their flow behavior and enhancing their effectiveness in different industries.
Ekene Onyiriuka
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Load Forecasting Techniques for Power System: Research Challenges and Survey
IEEE Access, 2022 The main and pivot part of electric companies is the load forecasting. Decision-makers and think tank of power sectors should forecast the future need of electricity with large accuracy and small error to give uninterrupted and free of load shedding ...
Naqash Ahmad +3 more
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A Prediction Model of Power Consumption in Smart City Using Hybrid Deep Learning Algorithm
JOIV: International Journal on Informatics Visualization, 2023 A smart city utilizes vast data collected through electronic methods, such as sensors and cameras, to improve daily life by managing resources and providing services. Moving towards a smart grid is a step in realizing this concept.
Salam Abdulkhaleq Noaman +2 more
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